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Rewrite Python built-in class `super()` calls. Only non-semantic changes should be applied. - #94587 - #94588 - #94592 Also, methods with only a `super()` call are removed: ```diff class MyModule(nn.Module): - def __init__(self): - super().__init__() - def forward(self, ...): ... ``` Some cases that change the semantics should be kept unchanged. E.g.:f152a79be9/caffe2/python/net_printer.py (L184-L190)f152a79be9/test/test_jit_fuser_te.py (L2628-L2635)Pull Request resolved: https://github.com/pytorch/pytorch/pull/94587 Approved by: https://github.com/ezyang
54 lines
1.3 KiB
Python
54 lines
1.3 KiB
Python
## @package sampling_trainable_mixin
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# Module caffe2.python.layers.sampling_trainable_mixin
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import abc
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class SamplingTrainableMixin(metaclass=abc.ABCMeta):
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self._train_param_blobs = None
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self._train_param_blobs_frozen = False
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@property
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@abc.abstractmethod
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def param_blobs(self):
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"""
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List of parameter blobs for prediction net
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"""
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pass
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@property
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def train_param_blobs(self):
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"""
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If train_param_blobs is not set before used, default to param_blobs
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"""
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if self._train_param_blobs is None:
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self.train_param_blobs = self.param_blobs
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return self._train_param_blobs
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@train_param_blobs.setter
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def train_param_blobs(self, blobs):
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assert not self._train_param_blobs_frozen
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assert blobs is not None
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self._train_param_blobs_frozen = True
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self._train_param_blobs = blobs
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@abc.abstractmethod
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def _add_ops(self, net, param_blobs):
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"""
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Add ops to the given net, using the given param_blobs
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"""
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pass
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def add_ops(self, net):
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self._add_ops(net, self.param_blobs)
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def add_train_ops(self, net):
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self._add_ops(net, self.train_param_blobs)
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